Tutorial 5
Fatimah Nizam
4/18/2021
Choose the dataset “attitude” from the R Datasets Package.
x <- datasets::attitude
x## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46
## 16 81 90 50 72 60 54 36
## 17 74 85 64 69 79 79 63
## 18 65 60 65 75 55 80 60
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39- See basic descriptive statistics
Run the function and observe the output, paste your output here.
- What is the difference between (attitude[3]) and (attitude$learning)
x[3]## privileges
## 1 30
## 2 51
## 3 68
## 4 45
## 5 56
## 6 49
## 7 42
## 8 50
## 9 72
## 10 45
## 11 53
## 12 47
## 13 57
## 14 83
## 15 54
## 16 50
## 17 64
## 18 65
## 19 46
## 20 68
## 21 33
## 22 52
## 23 52
## 24 42
## 25 42
## 26 66
## 27 58
## 28 44
## 29 71
## 30 39All of the data column are stored as a table.
x$learning## [1] 39 54 69 47 66 44 56 55 67 47 58 39 42 45 72 72 69 75 57 54 34 62 50 58 48
## [26] 63 74 45 71 59Stored as factors. 2. Lists name of variables in a dataset
ls(x)## [1] "advance" "complaints" "critical" "learning" "privileges"
## [6] "raises" "rating"- Calculate number of rows in a dataset
nrow(x)## [1] 30- Calculate number of columns in a dataset
ncol(x)## [1] 7- List structure of a dataset
str(x)## 'data.frame': 30 obs. of 7 variables:
## $ rating : num 43 63 71 61 81 43 58 71 72 67 ...
## $ complaints: num 51 64 70 63 78 55 67 75 82 61 ...
## $ privileges: num 30 51 68 45 56 49 42 50 72 45 ...
## $ learning : num 39 54 69 47 66 44 56 55 67 47 ...
## $ raises : num 61 63 76 54 71 54 66 70 71 62 ...
## $ critical : num 92 73 86 84 83 49 68 66 83 80 ...
## $ advance : num 45 47 48 35 47 34 35 41 31 41 ...- See first 6 rows (by default) of dataset
head(x)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34- See first n rows of dataset Select to see the first 15 rows of dataset
head(x, 15)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46- See all rows but the last row
head(x, n=-1)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46
## 16 81 90 50 72 60 54 36
## 17 74 85 64 69 79 79 63
## 18 65 60 65 75 55 80 60
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55- See last 6 rows (by default) of a dataset
tail(x)## rating complaints privileges learning raises critical advance
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39- See last n rows of dataset Select to see the last 12 rows of dataset.
tail(x,12)## rating complaints privileges learning raises critical advance
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39- See the last n rows but the first row
tail(x,5)## rating complaints privileges learning raises critical advance
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39- Number of missing values
sapply(attitude, function(x) sum(is.na(x)))## rating complaints privileges learning raises critical advance
## 0 0 0 0 0 0 0- Number of missing values in a single variable
sum(is.na(x$privileges))## [1] 0- Plot a simple graph, which will appear on a screen device.
with(attitude, plot(learning,privileges, main = "Learning Attitude"))
- Plot the graph shown below, and make it appear on a file device (a pdf file)
pdf(file="myplot.pdf")
with(x, plot(privileges, learning, main="Learning Attitude"))
dev.off()## png
## 2